clearence and data preparation
rm(list = ls())
library(dendextend)
##
## ---------------------
## Welcome to dendextend version 1.8.0
## Type citation('dendextend') for how to cite the package.
##
## Type browseVignettes(package = 'dendextend') for the package vignette.
## The github page is: https://github.com/talgalili/dendextend/
##
## Suggestions and bug-reports can be submitted at: https://github.com/talgalili/dendextend/issues
## Or contact: <tal.galili@gmail.com>
##
## To suppress this message use: suppressPackageStartupMessages(library(dendextend))
## ---------------------
##
## Attaching package: 'dendextend'
## The following object is masked from 'package:stats':
##
## cutree
#loading data
load('/home/mikhail/Telegram Desktop/matrix_2002.Rdata')
#exploring the data
str(dist_matrix_2002); class(dist_matrix_2002)
## num [1:1273, 1:1273] 0 68727 49370 33879 24615 ...
## [1] "matrix"
#coercing to dist object
dist_2002 <- as.dist(dist_matrix_2002)
Heirarchical clusterization using all the methods available (“ward.D”, “ward.D2”, “single”, “complete”, “average” (= UPGMA), “mcquitty” (= WPGMA), “median” (= WPGMC) or “centroid”)
methods <- c("ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median", "centroid")
for (i in methods){
for (j in methods){
if (i == j){next} else {#no identical dendrograms comparison is needed
hclusted_tmp1 <- hclust(dist_2002, method = i)
hclusted_tmp1 %>% as.dendrogram %>% set('labels_cex', 1e-9) -> dend_tmp1
hclusted_tmp2 <- hclust(dist_2002, method = j)
hclusted_tmp2 %>% as.dendrogram %>% set('labels_cex', 1e-9) -> dend_tmp2
ccc_tmp <- round(cor_cophenetic(dend_tmp1, dend_tmp2), digits = 2)
tanglegram(dend_tmp1, dend_tmp2, main_left = paste("2002 data\n ", i, "method"), main_right = paste("2002 data\n ", j, "method"), main = paste('CCC = ', ccc_tmp))
#print(paste(i, j))
}
}
}